Work

On the Value of Data: Multi-Objective Maximization of Value Creation in Data-Driven Industrial Services

Year: 2022

Type: conference-paper

Abstract: Data-driven value creation is a key topic in industrial services. However, designing such services in an optimal way represents a multidimensional and complex task. In this paper, we present a design methodology based on a simultaneous maxi-mization of value creation for both the provider and the customer, allowing the identification of optimal service configurations. We apply this methodology to a use case of a manufacturer delivering services for its machines in the context of a pay-per-use business model. The approach is based on modeling the value creation separately for both provider and customer, as a function of data-driven services which may be offered in different phases of the lifecycle. The model allows finding Pareto-optimal service configurations which provide value creation optimized simultaneously for both the provider and the customer. These optimal configurations are not easy to find with simpler methods because of non-linear effects in value creation along the lifecycle.

Source: IEEE Swiss Conference on Data Science (SDS)

DOI: 10.1109/sds54800.2022.00013

Authors: Jurg Meierhofer, Rodolfo Benedech, Christoph Heitz

Institution: ZHAW Zurich University of Applied Sciences

Language: English

Topic: Service and Product Innovation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funder: European Regional Development Fund